CN113298629B - Data sharing method based on two-way auction theory and intelligent contract - Google Patents
Data sharing method based on two-way auction theory and intelligent contract Download PDFInfo
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Abstract
The invention belongs to the technical field of data sharing, and particularly relates to a data sharing method based on a bidirectional auction theory and an intelligent contract. The data sharing method is used as a method for improving the participation enthusiasm of users and the long-term stable operation of the system through the selection of transaction parties and the balanced distribution of interests, and aims to ensure that all participants can obtain higher interests and the data sharing system can continuously operate. The traditional data sharing method is excessively concerned about the benefits of a third party platform supporting the operation of a data sharing system, the effectiveness of the two parties actually participating in sharing is low, the sharing enthusiasm is insufficient, and the sharing range is small. The method can be applied to long-term self-operation of the massive data sharing alliance blockchain system without an operator, has higher participant utility, blockchain network utility and system social benefit, and can realize distributed long-term massive data sharing without the participation of the operator.
Description
Technical Field
The invention belongs to the technical field of data sharing, and particularly relates to a data sharing method based on a bidirectional auction theory and an intelligent contract.
Background
With the increasing popularity of the internet of things, the number of internet of things devices such as sensors and intelligent devices has grown at a striking rate. Massive Internet of things data are generated by massive Internet of things equipment, but are stored in an isolated data center mode due to the lack of trust, benefit distribution and other problems, and cannot be shared by other people who are also required. The advent and development of blockchain technology provides a feasible sharing scheme for mass data sharing of the P2P Internet of things.
Blockchain-based data sharing systems are generally divided into two categories. The third party sharing (transaction) platform directly participates in, is responsible for the operation of the whole blockchain network, and aims to obtain benefits as much as possible, and the data sharing system is still not a complete P2P organization system structurally, so that the defects of the centralized platform are not completely avoided. The other is to construct a trust environment by using the blockchain, and use the blockchain as a tamper-proof and deletion-proof data certificate in data sharing (transaction), and perform user sharing incentive through the honest trusted environment and economic incentive through the tokens to further stimulate data sharing. Although no third party is directly involved, the token ecology requires someone to operate and maintain, is not fundamentally free from operators, and from the economic point of view, a one-taste subsidy scheme cannot operate for a long time.
Disclosure of Invention
The invention aims to provide a data sharing method based on a two-way auction theory and an intelligent contract.
The aim of the invention is realized by the following technical scheme: the method comprises the following steps:
step 1: group data requestor r= { R 1 ,r 2 ,…,r M Submitting their own request data type information to the smart contract, including a unit task assessment value; a set of data providers s= { S 1 ,s 2 ,…,s N Submitting their own data information to the smart contract, including unit data cost and quality; the intelligent contract estimates the data quality according to the historical submitted data quality stored in the blockchain, and adds the data quality to corresponding data information; wherein a requestor r i Only one task T can be submitted i A data provider s j Only one task can be accepted;
step 2: the smart contract selects a subset of the set of data requesters R as winning data requesters and a subset of the set of data providers S as winning data providers;
winning data requester selection: selecting a data requester with the largest unit task evaluation value; repeating such a selection process until the number of data requesters reaches a maximum amount of transactions that can be processed at one time by the data sharing network, or each data requester is selected;
winning data provider selection: selecting a data provider with low unit data cost and high quality; at each iteration, the data cost to historical quality ratio of the data provider is selectedThe smallest one serves as the winner; repeating such a selection process until the number of data providers reaches a maximum amount of transactions that the data sharing network can handle at a time, or each data provider is selected; wherein β is an adjustable parameter value for adjusting at c j And lambda (lambda) j The impact weight between the winner selections;
step 3: if the number of winning data requesters matches the number of winning data providers, i.e. one data requester corresponds to one data provider, step 4 is performed; otherwise, executing the step 5;
step 4: matching each data requester to a data provider according to a greedy algorithm; if the utility of the data requester, the utility of the data provider and the utility of the blockchain network obtained by calculating the final matching matrix are all non-negative values, the matching is successful, the step 6 is executed, otherwise, the step 7 is executed;
at each iteration, winning data requesters with maximum unit task evaluation values and minimum units having not been matched yetWinning data provider matching of the ratio;
step 5: pruning the party with more number, if the number of the winning data requesters is more, sorting according to the unit task evaluation values, and removing from the beginning with the lowest unit task evaluation value until the number of the remaining winning data requesters and the winning data are obtainedThe number of providers is consistent; if the winning data provider is more, the data cost and the historical quality ratio are selected according to the lowest unit data cost and the historical data quality to carry out comprehensive assessmentThe highest elimination is performed until the remaining winning data providers are consistent with the number of winning data requesters; after trimming, checking whether budget balance is established, namely that not all participants and the data sharing blockchain network can obtain positive utility, if so, starting a matching process, and executing step 6;
step 6: according to the matching result, benefit distribution is carried out; calculating for each winning data requester the fee q to be paid i And calculates a benefit p for each data provider j The method comprises the steps of carrying out a first treatment on the surface of the The winning data requester submits the virtual currency of the corresponding value to the intelligent contract according to the calculated expense, the intelligent contract pays the virtual currency to the winning data provider according to the calculated income, the winning data provider submits the data to the matched winning data requester, the winning data requester carries out real data quality feedback on the received data, the intelligent contract carries out comprehensive calculation according to the received data evaluation and the historical data quality, calculates a new data quality predicted value and stores the new data quality predicted value into the blockchain.
Wherein for q i And p j Using unit task evaluation value and ratio valueThereby making q i And p j Becomes a key value for guaranteeing the authenticity;
step 7: and (3) finishing one transaction, returning to the step (1), and carrying out the next transaction.
The invention has the beneficial effects that:
the invention provides a data sharing method based on a bidirectional auction theory and an intelligent contract, which can be applied to long-term self-operation of a massive data sharing alliance blockchain system without an operator, has higher participator utility, blockchain network utility and system social benefit, and can realize distributed long-term massive data sharing without participation of the operator.
Drawings
FIG. 1 is a model diagram of a data sharing federated blockchain system in the present invention.
Fig. 2 is a schematic flow chart of the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
The invention relates to a data sharing method based on a bidirectional auction theory and an intelligent contract, which is applied to long-term self-operation of a massive data sharing alliance block chain system without an operator.
The data sharing method is used as a method for improving the participation enthusiasm of users and the long-term stable operation of the system through the selection of transaction parties and the balanced distribution of interests, and aims to ensure that all participants can obtain higher interests and the data sharing system can continuously operate. The traditional data sharing method is excessively concerned about the benefits of a third party platform supporting the operation of a data sharing system, the effectiveness of the two parties actually participating in sharing is low, the sharing enthusiasm is insufficient, and the sharing range is small. The invention provides a data sharing method based on a two-way auction theory and an intelligent contract, which enables the method to have higher participant utility, blockchain network utility and system social benefit in a long-term competition environment, and can be used for distributed long-term mass data sharing without the participation of operators. The invention comprises the following steps:
step 1) a group of data requesters submit their own request data type information to the smart contract, including maximum task assessment, deadlines, etc. Similarly, a group of data providers submit their own data information to the intelligent contract, the information containing their cost values, the intelligent contract estimates this data quality from the historical submitted data quality stored by the blockchain, and adds it to the corresponding data information;
step 2) the intelligent contract selects a subset of the data requesters as winning requesters according to a certain rule, and a subset of the data providers as winning workers;
if the number of winning data requesters matches the number of data providers, i.e. one data requester corresponds to one data provider, go to step 3), otherwise go to step 4);
step 3) matching each data requester to a data provider according to a greedy algorithm;
if the utility of the data requester, the utility of the data provider and the utility of the blockchain network obtained by calculating the final matching matrix are all non-negative values, the matching is successful, and the step 4) is switched to, otherwise, the step 6) is switched to;
step 4) pruning the party with more numbers, if the party with more numbers is the data requester, sorting according to the unit data evaluation values, and removing from the beginning of the lowest unit data evaluation value until the number of the rest people is consistent with the number of the data providers; if the number of the data providers is large, comprehensively evaluating according to the lowest unit data cost and the quality of the historical data, and selecting the elimination with the highest ratio of the cost to the historical quality until the number of the rest people is consistent with the number of the data requesters;
step 5), according to the matching result, benefit distribution is carried out;
step 6) completing one transaction.
FIG. 1 depicts a blockchain-based data sharing business model. It illustrates how data sharing and revenue distribution is achieved through information interaction and capital flow. Data providers hold various types of data and share their data across a blockchain network when data requests are made by data requesters. Generally, data is encrypted prior to uploading to protect privacy. The data requester pays a fee after acquiring the data, which is ultimately distributed to the data provider providing the relevant data and the blockchain mining node facilitating the information interaction. The present invention utilizes smart contracts to automatically control revenue distribution. The smart contract may be considered a trusted intermediary that performs payment terms and manages the flow of funds. In this business model, participants will be continuously rewarded as new revenue flows into the federation. This form of revenue distribution seems more reasonable because it motivates participants to be responsible for the outcome of the outcome.
The data sharing system is composed of a block chain network, a group of M data requesters (data purchasers) R= { R 1 ,r 2 ,…,r M A group of N data providers (data sellers) s= { S 1 ,s 2 ,…,s N }. The internet of things device or user may be either a requestor or a blockchain-based data sharing system data provider. For simplicity, assume a requestor r i Only one task T can be submitted i A data provider s j Only one task can be accepted. In real world data sharing systems, it is assumed that a blockchain network is limited in its ability to handle task requests simultaneously. In the proposed incentive contract, the process of data sharing (trading) is in the form of a double auction, with data requesters (data providers) competing with each other, selected as winning data requesters (data providers), to complete the trade, as shown in fig. 2.
1) Winning data requester selection: the data requesters whose unit task evaluation values are large are selected, and such a selection process is repeated until the number of data requesters reaches the maximum amount of transactions that can be processed at one time by the data sharing network, or each data requester is selected.
2) Winning data provider selection: data providers with low task value and high data quality are selected. At each iteration, the data cost to historical quality ratio of the data provider is selectedThe smallest one is used as winner, beta is an adjustable parameter value for adjusting the parameter value in c j And lambda (lambda) j The impact weight on winner selection. By using this ratio, it attempts to select a data provider that is of high data quality and low cost. Such a selection process is repeated until the number of data providers reaches the maximum amount of transactions that the data sharing network can handle at a time, or each data provider is selected.
3) Before matching data requesters and data providers, the intelligent contract automatically checks whether the data requesters and data providers can be matched one-to-one, if the two sets are not identical in size, the winning sets of the data requesters and the data providers are replaced by running a pruning method, in the pruning method, the winner sets returned in the step 1) and the step 2) are subjected to fine tuning, so that the winning data requester sets and the data provider sets have the same size, after pruning, whether budget balance is established is checked, namely whether all participants and the data sharing blockchain network can be positively utilized, and if so, the matching process is started.
3) Matching: iteratively matching winning data requesters with winning data providers, winning data requesters having maximum unit task valuations that have not been matched and winning data requesters having minimum units task valuationsThe winning data provider of the ratio is matched by matching a data requester with a higher data request task fee with a data provider with a lower cost and higher data quality by such a matching criterion.
4) After the matching process, the fee q to be paid is calculated for each winning data requester i And calculates a benefit p for each data provider j . For q i And p j Using unit task evaluation value and ratio valueThereby making q i And p j Becomes a key value to ensure the authenticity of the requester.
5) The data requester submits the virtual currency with corresponding value to the intelligent contract according to the calculated expense, the intelligent contract pays the virtual currency to the data provider according to the calculated income, the data provider submits the data to the matched data requester, the data requester carries out real data quality feedback on the received data, the intelligent contract carries out comprehensive calculation according to the received data evaluation and the historical data quality, calculates a new data quality estimated value and stores the new data quality estimated value into the blockchain.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (1)
1. The data sharing method based on the two-way auction theory and the intelligent contract is characterized by comprising the following steps:
step 1: group data requestor r= { R 1 ,r 2 ,…,r M Submitting their own request data type information to the smart contract, including a unit task assessment value; a set of data providers s= { S 1 ,s 2 ,…,s N Submitting their own data information to the smart contract, including unit data cost and quality; the intelligent contract estimates the data quality according to the historical submitted data quality stored in the blockchain, and adds the data quality to corresponding data information; wherein a requestor r i Only one task T can be submitted i A data provider s j Only one task can be accepted;
step 2: the smart contract selects a subset of the set of data requesters R as winning data requesters and a subset of the set of data providers S as winning data providers;
winning data requester selection: selecting a data requester with the largest unit task evaluation value; repeating such a selection process until the number of data requesters reaches a maximum amount of transactions that can be processed at one time by the data sharing network, or each data requester is selected;
winning data provider selection: selecting a data provider with low unit data cost and high quality; at each iteration, the data cost to historical quality ratio of the data provider is selectedThe smallest one serves as the winner; repeating such selectionThe process until the number of data providers reaches the maximum amount of transactions that can be processed at one time by the data sharing network, or each data provider is selected; wherein β is an adjustable parameter value for adjusting at c j And lambda (lambda) j The impact weight between the winner selections;
step 3: if the number of winning data requesters matches the number of winning data providers, i.e. one data requester corresponds to one data provider, step 4 is performed; otherwise, executing the step 5;
step 4: matching each data requester to a data provider according to a greedy algorithm; if the utility of the data requester, the utility of the data provider and the utility of the blockchain network obtained by calculating the final matching matrix are all non-negative values, the matching is successful, the step 6 is executed, otherwise, the step 7 is executed;
at each iteration, winning data requesters with maximum unit task evaluation values and minimum units having not been matched yetWinning data provider matching of the ratio;
step 5: pruning the party with more winning data requesters, sorting according to the unit task evaluation values if the winning data requesters are more, and removing from the beginning with the lowest unit task evaluation value until the number of the remaining winning data requesters is consistent with the number of the winning data providers; if the winning data provider is more, the data cost and the historical quality ratio are selected according to the lowest unit data cost and the historical data quality to carry out comprehensive assessmentThe highest elimination is performed until the remaining winning data providers are consistent with the number of winning data requesters; after trimming, checking whether budget balance is established, namely that not all participants and the data sharing blockchain network can obtain positive utility, if so, starting a matching process, and executing step 6;
step 6: according to the matching result, benefit distribution is carried out; for each ofThe winning data requester calculates the fee q to be paid i And calculates a benefit p for each data provider j The method comprises the steps of carrying out a first treatment on the surface of the The winning data requester submits the virtual currency of the corresponding value to the intelligent contract according to the calculated expense, the intelligent contract pays the virtual currency to the winning data provider according to the calculated income, the winning data provider submits the data to the matched winning data requester, the winning data requester carries out real data quality feedback on the received data, the intelligent contract carries out comprehensive calculation according to the received data evaluation and the historical data quality, calculates a new data quality predicted value and stores the new data quality predicted value into the blockchain;
wherein for q i And p j Using unit task evaluation value and ratio valueThereby making q i And p j Becomes a key value for guaranteeing the authenticity;
step 7: and (3) finishing one transaction, returning to the step (1), and carrying out the next transaction.
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